With the development of society and technology, mobile terminals such as mobile phones are used more and more widely. Among numerous mobile phones, smart phones based on operating systems such as Android and iOS (the operating system for handheld devices developed by Apple Inc.) become more and more popular, which provide a variety of applications for users, thus making the life and work of users more convenient. A big problem of mobile terminals such as smart phones is the limited battery life, which does not only affect user experience, but also constrains the emergence of more attractive and complex applications.
In cellular networks, it has already been proved that radio resources shared among mobile terminals consume the most battery energy of mobile terminals. However, more than 60% of the energy consumed by radio resources is derived from the timeout periods of inactivity timers. The inactivity timers are configured to control the release of radio resources. Accordingly, the timeout period of inactivity timers is referred to as the tail time. The tail time is adopted to seek a balance between radio resources, user experience, energy consumption and network overhead. However, the tail time results in the wastage of radio resources and battery energy of mobile terminals. Taking the 3G network and the Universal Mobile Telecommunications System (UMTS) as an example, in order to use the limited radio resources more effectively, the UMTS adopts a Radio Resource Control (RRC) protocol. The RRC protocol maintains a common state machine for both the mobile terminal and Radio Network Controller (RNC). In different states of the RRC state machine, the mobile terminal consumes different levels of battery energy. Before data is transmitted, the state of the RRC state machine is promoted to a high power state. It should be noted that the state promotion does not only consume energy, but also brings a certain delay to the user. When the data transmission is completed, the state of the RRC state machine is not demoted to a low power state immediately. Instead, the RRC state machine waits for a certain duration (the tail time, which is reaches up to 15 seconds) according to the inactivity timers. During this period, there is no data transmission, but the mobile terminal is still in the high power state, thus wasting battery energy of the mobile terminal.
FIG. 1 shows an overview of the RRC state machine of the UMTS. The RRC state machine has three different states which are the dedicated channel state, the forward access channel state and the idle state. The dedicated channel state and the forward access channel state are in a connection state, and under which the mobile terminal is able to transmit data. However, the mobile terminal is unable to transmit data under the idle state. In addition, the three different states correspond to different levels of energy consumption, in which the dedicated channel state consumes the most energy. When the mobile terminal has data to be transmitted or received, the RRC state machine promotes from the idle state to the dedicated channel state. As this state promotion process needs to apply for resource from the RNC, a certain time (promotion time, which is about 2 seconds) is consumed. After the data are transmitted, the RNC starts an inactivity timer α (corresponding to time T1). When the timer α is timeout, the RRC state machine is demoted from the dedicated channel state to the forward access channel state. In the forward access channel state, when either the uplink buffer or the downlink buffer exceeds a threshold set by the RNC, the state of the RRC state machine will be promoted from the forward access channel state to the dedicated channel state. If there is still no data transmission in the forward access channel state, the RNC will start another inactivity timer β (corresponding to time T2). When the timer β is timeout, the state of the RRC state machine will be demoted to the idle state. Furthermore, it is possible to demote from the dedicated channel state to the idle state by an operation which is called fast dormancy.
In order to solve the problem that the tail time in cellular networks causes waste of battery energy of mobile terminals, investigators proposed a plurality of optimization methods. According to the difference in dealing the tail time, these optimization methods can be classified into two types: traffic aggregation method and tail time tuning method. The traffic aggregation method aggregates small transmissions into a large continuous transmission according to the traffic patterns of transmissions so as to reduce the occurrence number of the tail time and the energy consumption for transmitting data. One example of the traffic aggregation method is TailEnder (refer to Naianjan Balasubramanian. etc, “Power Consumption in Mobile Phones: A Measurement Study and Implications for Network Applications”, 2009, Internet Measurement Conference). For delay-tolerant applications (such as e-mails and RSS) and prefetchable applications (such as news and videos), the traffic aggregation method can aggregate traffic by deferring and prefetching. However, when the prefetching accuracy of the prefetchable applications is very low, the traffic aggregation method not only does not reduce the energy consumption, but increases the energy consumption. For example, when only a very small portion of prefetched data is necessary for prefetchable applications, the traffic aggregation method only reduces a very small portion of the tail time, but consumes great power for the prefetching operation itself. The tail time tuning method is desirable to seek a balance between the energy consumption in the tail time and the delays brought by state promotions of different RRC states. Most of these tail time tuning methods are desirable to find an appropriate length of the tail time. However, even if an appropriate length of the tail time is set, the tail time still exists and brings considerable energy wastage. One recently proposed tail time tuning method is TOP (refer to Feng Qian, etc, “TOP: Tail Optimization Protocol for Cellular Radio Resource Allocation”, 2010, IEEE International Conference on Network Protocols), which takes advantage of a feature called fast dormancy to dynamically terminate the tail time. When TOP predicts that there is no data needed to be transmitted in a period of time in the future, it quickly demotes the state of the RRC state machine to the low power state. However, the effectiveness of TOP depends on the accuracy of the prediction of future traffic patterns. Low prediction accuracy brings extra state promotions, thus bringing more waste of battery energy of mobile terminals.
In conclusion, the tail time in cellular networks consumes a large portion of battery energy of mobile terminals, and the battery life of mobile terminals can be improved by optimizing the tail time. However, in some cases, the previously proposed methods for optimizing the tail time not only cannot save battery energy, but increase energy consumption of mobile terminals.